Hello! I am having problems with kedro-mlflow. I am running a pipeline (pipeline-name) which terminates without giving any errors. The problem comes when I access the mlflow ui where two runs are shown, on one side the pipeline-name run and on the other side a run with a random name. In the pipeline-name run the model is logged but no parameters are shown, on the other hand in the run with the arbitrary name if the hyperparameters of the model are registered. Moreover, this run never ends even when the execution of the pipeline is finished. Does anyone know what could be happening? Thank you!

Someone will reply to you shortly. In the meantime, this might help:

Hey @Martin Gonzalez, would be helpful if you could share some error logs/screenshots or a repo with which I could reproduce this?

Could you explain a bit more about the parameters? They’re not coming from the

conf/base/parameters.yml

but somewhere else?

node(
    func=fit_xgboost,
    name='fit_xgboost',
    inputs=['X_train', 'y_train', 'params:xgboost_conf'],
    outputs='XGBRegressor',
)

No, the parameters are from

conf/base/parameters.yml

So if there’s a

params:something

in the pipeline inputs, it’s creating a spurious run but not otherwise?

yes

Okay, I’ll try this out and get back to you. CCing @Yolan Honoré-Rougé incase you have any insights

Hi can you give your kedro /mlflow /kedro mlflow versions?

i have the same issue

kedro==0.19.11
kedro-mlflow==0.14.0
mlflow==2.20.1

Just tested with

kedro==0.19.10

and it works fine

downgrading kedro to 0.19.10 solves the issue

Wow very surprising, this type of error usually comes from mlflow or kedro-mlflow, not kedro.

@Yolan Honoré-Rougé yes, I was using the sequential runner

Thanks for looking into this @Yolan Honoré-Rougé, i’ll try to figure out what’s going on on Kedro side today!

@Martin Gonzalez Can you try with

pip install kedro-mlflow==0.14.3

? It should be fixed